The Empirical Research on Volatility Measurement Model Based Multiplicative Error Model

Author

Yulin Ma ; Pin Guo ; Yuan Zhao

Author_Institution

Sch. of Mathematic & Quantitative Econ., Shandong Univ. of Finance & Econ., Jinan, China

fYear

2014

fDate

4-6 July 2014

Firstpage

455

Lastpage

458

Abstract

Volatility is a very important factor of measuring financial risk. This paper introduces the volatility measurement method of high frequency financial time series involving the nonnegative-Multiplicative Error Model. This paper takes the high frequency data of HS300 index of Chinese stock market as the research object, building the TARCH model according to leverage, and uses the "realized volatility" to build ARFIMA model, multiplicative error model respectively, then carries on the comparative analysis on accuracy after using the three models to predict with the mean square error method. The analysis results show that the multiplicative error model gives the best prediction effects, and ARFIMA model is the second.

Keywords

autoregressive moving average processes; mean square error methods; risk management; stock markets; time series; ARFIMA model; Chinese stock market; HS300 index; TARCH model; financial risk; fractional integrated autoregressive moving average models; high frequency data; high frequency financial time series; mean square error method; nonnegative multiplicative error model; prediction effects; realized volatility; volatility measurement model; Analytical models; Data models; Frequency measurement; Indexes; Measurement uncertainty; Predictive models; Time series analysis;

fLanguage

English

Publisher

ieee

Conference_Titel

Computational Sciences and Optimization (CSO), 2014 Seventh International Joint Conference on

Conference_Location

Beijing

Print_ISBN

978-1-4799-5371-4

Type

conf

DOI

10.1109/CSO.2014.156

Filename

6923724